Data stream mining
Data streaming is one area of data mining that has been studied extensively. One problem of data streaming is to detect noise and random shapes when clustering, where basic K-Means usually fail. Some researchers suggested density based clustering according to a decay function; one typical example is...
Saved in:
Main Author: | Huang, Lelun. |
---|---|
Other Authors: | Ng Wee Keong |
Format: | Final Year Project |
Language: | English |
Published: |
2010
|
Subjects: | |
Online Access: | http://hdl.handle.net/10356/36246 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Data stream mining
by: Wan, Li
Published: (2009) -
Concurrent data stream mining
by: Wang, Wenwen.
Published: (2009) -
Approximation algorithms for mining patterns from data streams
by: Dang, Xuan Hong
Published: (2008) -
Query processing in publish/subscribe systems for textual data streams
by: Chen, Lisi
Published: (2016) -
Data mining for customer service support
by: Jha, Gunjan
Published: (2008)